EGUIDE:
The emphasis on home and remote working has been felt in storage and backup as in all areas of IT, with continued evolution towards the cloud and as-a-service storage and backup.
TECHNICAL ARTICLE:
View this post to learn about the four types of data abstractions that Windows Azure Storage (WAS) offers for applications developers: blobs, tables, queues, and drives. Then learn about how they are partitioned, the URIs for each, and their scalability targets.
EGUIDE:
This e-guide helps guide organizations toward a flash system that won't break the bank. Read on about things to consider when choosing from the many all-flash array products, and find the match for your organization.
WHITE PAPER:
This white paper explains the benefits of a solution that combines the unique capabilities of flash storage and software-defined storage. By combining the easy management of software-definied storage with the scalable performance of flash, organizations can easily meet their growing storage requirements.
CASE STUDY:
This case study describes how one organization faced business growth and increased IT demands with a new approach to storage that delivered reduced complexities and space savings as well as increased efficiency and easy management.
WHITE PAPER:
You need to maximize server virtualization efficiency, and doing so depends on choosing the right storage architecture. Check out this 2-page white paper to learn how.
WHITE PAPER:
This informative guide explains the new usage cases for tape storage in the data center. It explains the circumstances that have led to a need for new tape storage technologies and then goes on to explain the benefits of one suite of solutions.
WHITE PAPER:
Storage capacity utilization metrics provide a framework you can use to analyze and manage SAN storage use across a diverse IT environment. Check out this white paper to explore how capacity metrics can help your organization with efficiency, capacity management, and risk management.
WHITE PAPER:
Many enterprises rely on Hadoop to manage and analyze large volumes of data, and as such, they are looking to deploy the right architecture to optimize compute and storage requirements. The traditional approach is running Hadoop on DAS -- but is there a better way?
